The present invention relates to devices for detecting or measuring degradation of materials or structures, and more particularly to acoustic emission monitoring devices for detecting incipient fatigue damage in materials or structures.
Acoustic emission is a nondestructive testing technique which reacts to the active behavior of defect growth in structures and materials, such as occurs during fatiguing. This technique exploits the fact that any material will tend towards the lowest possible energy state. If a defect such as a microfracture is present in the material, it will have the effect of causing a localized increase in energy, resulting in defect growth when the material reacts to achieve a lower energy state. Coincident with this growth, a stress wave (also referred to as an acoustic emission) will propagate through the material, with the defect being the epicenter of the stress wave. Thus, detection of such a wave indicates that a growing defect is present in the material. Also, since the growing defect itself creates the stress wave, the characteristics of the stress wave are dependent upon the nature of the defect, so that monitoring of acoustic emissions produced by material defects can provide information concerning progressive fatiguing or other cracking, and thus impending failure, of the material. Acoustic emission monitoring is extremely sensitive to small dynamic changes, such as subcritical crack growth, in the state of stress of materials. Unfortunately, this sensitivity means that there is a high probability of obtaining irrelevant information, such as background noise, with desired data. In addition, acoustic emission monitoring devices presently in use produce plots of acoustic emission rate or total acoustic emissions versus number of fatigue cycles. While such plots do show the variation in acoustic emission rate or in total acoustic emissions under progressive fatiguing, further interpretation of such data is highly limited, so that an analysis of microfracture processes in materials using this data would yield limited information.